Importing the libraries
library(ggplot2)
library(plotly)
##
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
##
## last_plot
## The following object is masked from 'package:stats':
##
## filter
## The following object is masked from 'package:graphics':
##
## layout
records creation
name = c("Prashanth", "Sam", "Rohan", "Daniel", "Siraj", "Dhoni", "Yuvraj", "Rohith")
age = c(20, 15, 30, 40, 30, 25, 43, 37)
weight = c(57, 69, 75, 70, 83, 53, 83, 90)
height = c(177, 163, 163, 183, 164, 190, 179, 182)
branch = c("Data Analytics", "Machine Learning Engineer", "Data Analytics", "Data Analytics", "Machine Learning Engineer",
"Business Intelligence Engineer", "Data warehousing Engineer", "Business Intelligence Engineer")
address = c("Chennai", "Madurai", "Punjab", "Salem", "Madurai", "Punjab", "Chennai", "Salem")
score = c(80, 90, 75, 60, 80, 95, 99, 56)
data-frame creation
df = data.frame (row.names = name, age, weight, height, branch, address, score)
head(df)
Bar Plot
bar_plot = ggplot(data=df, aes(x = branch, y = ..count.. / sum(..count..),fill = factor(branch))) +
geom_bar(color='black') +
labs(y = "Percentage of Branches chosen", title = "Percentage of the quality of the Branch") +
scale_y_continuous(labels = scales::percent) +
coord_flip()
ggplotly(bar_plot)
Histogram
histogram_plot = ggplot(data=df, aes(x=weight)) +
geom_histogram(color = "black",fill = "grey") +
labs(x = "Total Weight", y="Count", title="Count of Total Time asleep per day(h)") +
scale_x_discrete(labels =labs)
ggplotly(histogram_plot)
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Kernel Density Plot
density_plot = ggplot(data=df, aes(x = height)) +
geom_density(fill = "indianred3") +
labs(x = "height", y="density", title="Kernal density of the height")
ggplotly(density_plot)
Scatter plot
t <- list(family = "Helvetica",size = 14,color = "blue")
t1 <- list(family = "Times New Roman",color = "red")
t2 <- list(family = "Courier New",size = 14,color = "green")
t3 <- list(family = 'Arial')
fig_sp = plot_ly(data = df, x=height, y=weight, color = ~name,
type = 'scatter', mode = 'markers')%>%
layout(title= list(text = "Body weight vs Brain weight",font = t1), font=t,
legend = list(title=list(text='Animals',font = t2)),
xaxis = list(title = list(text ='Brain Weight', font = t3)),
yaxis = list(title = list(text ='Body Weight', font = t3)),
plot_bgcolor='#e5ecf6')
fig_sp
Pie-Chart
df_order = data.frame(table(df$address))
print(df_order)
## Var1 Freq
## 1 Chennai 2
## 2 Madurai 2
## 3 Punjab 2
## 4 Salem 2
fig_order = plot_ly(type='pie', labels=df_order$Var1, values=df_order$Freq,
textinfo='label+percent',insidetextorientation='radial')
fig_order